Familial Pulmonary Fibrosis

Another study at the Center for Genes, Environment and Health uses linkage analysis to identify loci which predispose individuals to the familial form of pulmonary fibrosis (familial interstitial pneumonia; FIP)1. High density microarrays allow a refined resolution of 2.7 kilobases between single nucleotide polymorphisms (SNPs). Computational analyses process the raw data for over 1 million SNPs, establish haplotypes, and compute LOD scores. Next-generation targeted resequencing of the associated loci can validate the identified SNPs and uncover additional potential disease-associated SNPs. Additional computational algorithms are then used to search against existing databases of known variants to determine the effect of a SNP, or to predict the potential deleterious effect of a novel SNP.

An SNP might disrupt gene expression, micro-RNA binding affinity or methylation capacity, each of which CGEH has planned to further investigate using the respective low and high-throughput technology. When SNP analysis implicates one or more potential disease-associated genes, additional bioinformatics analyses can help identify pathways affected by altered function of the genes.

Using resequencing of a locus identified in the FIP linkage study, CGEH identified a novel SNP residing in the upstream regulatory region of gene from a plausible lung-specific pathway and confirmed that the SNP occurs in 59 percent of familial and 66 percent of non-familial idiopathic interstitial pneumonia cases.

Functional implications of the SNP are being further investigated using gene expression studies. Computational algorithms are being developed at CGEH to create analysis pipelines like that illustrated in this example, facilitating CGEH's goal to establish the genetic, molecular, and quantitative clinical phenotypes underlying disease.